{"id":"W2012986875","doi":"10.1118/1.2756939","title":"Quantitative characterization of metastatic disease in the spine. Part II. Histogram‐based analyses","year":2007,"lang":"en","type":"article","venue":"Medical Physics","topic":"Management of metastatic bone disease","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Medicine; Voxel; Radiology; Bone disease; Histogram; Nuclear medicine; Medical imaging; Radiography; Pathology; Osteoporosis; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005024758,0.0002701547,0.0002366867,0.002073916,0.0001904293,0.0005287167,0.0002563709,0.0002636007,0.001333545],"category_scores_gemma":[0.001259012,0.0002035063,0.0003011281,0.0007936935,0.0004807106,0.0003528658,0.0002497842,0.0002514628,0.0003032627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003941658,"about_ca_system_score_gemma":0.0002307636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002504229,"about_ca_topic_score_gemma":0.002553219,"domain_scores_codex":[0.9997742,0.00004111266,0.00001326536,0.00003070955,0.0001210107,0.00001980312],"domain_scores_gemma":[0.9996044,0.0001810624,0.00007015569,0.00003633332,0.00008773251,0.00002034499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006312376,0.0001331066,0.05329287,0.000534245,0.0001394929,0.0002269592,0.0003252625,0.02581306,0.6954103,0.002393244,0.0009454975,0.2201548],"study_design_scores_gemma":[0.00004297279,0.000599072,0.6046719,0.00005401799,0.0001535067,0.002271716,0.0003236597,0.2005048,0.1799288,0.004216578,0.007133062,0.00009994893],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6916389,0.004885887,0.298844,0.0001271769,0.00003482039,0.00020631,0.001032885,0.0005927776,0.002637328],"genre_scores_gemma":[0.9520003,0.0009694356,0.04453345,0.0000310267,0.00002984663,0.0001380125,0.0008936104,0.00009936994,0.001304957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002504229,"threshold_uncertainty_score":0.004979312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0904440305940504,"score_gpt":0.3888858956261084,"score_spread":0.2984418650320579,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}